1 00:00:06,080 --> 00:00:12,760 Speaker 1: Her trains. I'm Joel Webber and I'm Eric. Eric. Today 2 00:00:12,760 --> 00:00:17,640 Speaker 1: we have an unusual guest and active e t F manager. Yeah, 3 00:00:17,680 --> 00:00:19,799 Speaker 1: I mean most of the money and the people in 4 00:00:19,840 --> 00:00:22,759 Speaker 1: ETFs are passive in fact, summer you know cult like 5 00:00:22,920 --> 00:00:26,599 Speaker 1: about their allegiance to passive. But here's an active manager 6 00:00:26,680 --> 00:00:29,360 Speaker 1: that has has been founding success and she's something of 7 00:00:29,400 --> 00:00:31,560 Speaker 1: a star. She We put her on the Bloomberg fifty 8 00:00:31,680 --> 00:00:36,360 Speaker 1: last year because she was such a phenomenal uh entrance 9 00:00:36,760 --> 00:00:40,120 Speaker 1: into finance and in a very unusual way. Yeah, and 10 00:00:40,240 --> 00:00:45,400 Speaker 1: I'm very excited. Um. She is completely bucking like many 11 00:00:45,479 --> 00:00:48,000 Speaker 1: trends at once. She is one of the hottest hands 12 00:00:48,040 --> 00:00:50,080 Speaker 1: in active management, and there aren't many hot hands. As 13 00:00:50,159 --> 00:00:53,280 Speaker 1: you know, active is struggling in all facets. It's under performing, 14 00:00:53,360 --> 00:00:58,680 Speaker 1: largely just eating everything. Stock pickers are just they're in essence, 15 00:00:58,680 --> 00:01:01,000 Speaker 1: they're facing an existential cry if you think about it. 16 00:01:01,320 --> 00:01:03,279 Speaker 1: But Cathy Wood came along a couple of years ago 17 00:01:03,440 --> 00:01:06,920 Speaker 1: and just really shocked the world by coming in and 18 00:01:07,040 --> 00:01:12,200 Speaker 1: getting a ton of inflows for being active, discretionary, high cost, 19 00:01:12,600 --> 00:01:15,240 Speaker 1: and she's an independent, no big distribution to help her. 20 00:01:16,520 --> 00:01:18,800 Speaker 1: She had different about t f s like talk like 21 00:01:19,080 --> 00:01:21,320 Speaker 1: it's like five hurdles stacked on on one another. And 22 00:01:21,440 --> 00:01:25,240 Speaker 1: she overcame that largely on great performance. That was part 23 00:01:25,280 --> 00:01:27,840 Speaker 1: of it. But what she does which is interesting, is 24 00:01:28,520 --> 00:01:32,399 Speaker 1: she just focuses on disruptive innovation. That's her main thing. 25 00:01:32,600 --> 00:01:36,120 Speaker 1: So she's active because, um, she don't get stuck in 26 00:01:36,280 --> 00:01:39,320 Speaker 1: one sector or one theme. She wanted a room to 27 00:01:39,400 --> 00:01:42,680 Speaker 1: move and she's a formerly an active manager. Um. And 28 00:01:42,880 --> 00:01:45,360 Speaker 1: in retrospect, I gotta say, it makes sense if you 29 00:01:45,400 --> 00:01:47,400 Speaker 1: are going after things that are moving quickly and you 30 00:01:47,440 --> 00:01:50,000 Speaker 1: have a strategy, Uh, it kind of makes sense to 31 00:01:50,040 --> 00:01:53,080 Speaker 1: be active in this space. She's also very thematic. What 32 00:01:53,320 --> 00:01:56,080 Speaker 1: are her et f s. The Arc Innovation e t 33 00:01:56,240 --> 00:01:57,760 Speaker 1: F which is a r k K that's the main 34 00:01:57,840 --> 00:01:59,840 Speaker 1: one that goes across all sectors. That's sort of like 35 00:01:59,880 --> 00:02:01,960 Speaker 1: the flagship product. But then she's got one called the 36 00:02:02,000 --> 00:02:06,560 Speaker 1: Genomic Revolution, web X point oh um, the Industrial Innovation, 37 00:02:06,920 --> 00:02:10,519 Speaker 1: Fintech Innovation, three D printing, and Israel Tech ETF. So 38 00:02:10,880 --> 00:02:12,760 Speaker 1: you can say that a common thread here, which is 39 00:02:13,320 --> 00:02:16,079 Speaker 1: she's in a way she is living and investing in 40 00:02:16,160 --> 00:02:18,760 Speaker 1: the future that's five years out. Yeah, when every time 41 00:02:18,800 --> 00:02:20,679 Speaker 1: I talked to her, I feel like I'm just a 42 00:02:20,760 --> 00:02:23,880 Speaker 1: little like um slow, like I'm not I need to 43 00:02:24,000 --> 00:02:26,720 Speaker 1: learn more about what's happening. She's really dynamic. She also 44 00:02:26,760 --> 00:02:29,440 Speaker 1: makes some big bets, one being the one that she's 45 00:02:29,440 --> 00:02:32,639 Speaker 1: probably most famous for. If you on the Twitter tes, yeah, 46 00:02:32,680 --> 00:02:34,600 Speaker 1: she she said Testa is going to four thousand dollars 47 00:02:34,639 --> 00:02:37,320 Speaker 1: in five years. That just riled up all of the 48 00:02:37,400 --> 00:02:40,239 Speaker 1: haters on social media and sopecially the year when the 49 00:02:40,720 --> 00:02:44,720 Speaker 1: stocks down or something. Yeah. I mean she's one of 50 00:02:44,760 --> 00:02:47,119 Speaker 1: the rare bulls out there, but she just and she's 51 00:02:47,160 --> 00:02:49,840 Speaker 1: been with it for a long thing. She owns the stock. 52 00:02:50,040 --> 00:02:51,720 Speaker 1: It's the top waiting in her fun I'm not sure 53 00:02:51,760 --> 00:02:54,200 Speaker 1: why people get so piste off when she's actually owning it. 54 00:02:54,280 --> 00:02:55,519 Speaker 1: I mean, it's not like she's just saying something she 55 00:02:55,600 --> 00:02:57,679 Speaker 1: hasn't known and she trades. It's not like it's not 56 00:02:57,800 --> 00:03:00,200 Speaker 1: like a buy and hole position. Yeah. And so she's 57 00:03:00,200 --> 00:03:02,240 Speaker 1: actually had Elon Musti has a podcast. She had Elon 58 00:03:02,320 --> 00:03:04,800 Speaker 1: Musk on her podcast. So I think he was happy 59 00:03:04,880 --> 00:03:06,840 Speaker 1: to find some people out there who were, you know, 60 00:03:07,200 --> 00:03:09,320 Speaker 1: with him, because there's a lot of haters of that stock. 61 00:03:09,400 --> 00:03:11,560 Speaker 1: But really with Kathy, one of the thing I want 62 00:03:11,600 --> 00:03:14,000 Speaker 1: to say is as we find that active is looking to, 63 00:03:14,200 --> 00:03:16,400 Speaker 1: you know, how to move forward in this passive world. 64 00:03:16,720 --> 00:03:20,160 Speaker 1: I think Kathy has developed one way forward, a blueprint, 65 00:03:20,240 --> 00:03:22,840 Speaker 1: which is to be high active share. Really you just 66 00:03:23,040 --> 00:03:26,040 Speaker 1: very concentrated going for the gold, so to speak, with 67 00:03:26,120 --> 00:03:29,600 Speaker 1: only like thirty stocks, a lot of bold bets, bold 68 00:03:29,680 --> 00:03:33,160 Speaker 1: calls like Tesla, high conviction, not wavering if the stock 69 00:03:33,200 --> 00:03:36,080 Speaker 1: goes down, and transparency shows her holdings every day, shows 70 00:03:36,080 --> 00:03:38,480 Speaker 1: her trades every day, She crowdsources research, and she got 71 00:03:38,560 --> 00:03:40,960 Speaker 1: a big social media presence pretty much all those things 72 00:03:41,040 --> 00:03:43,640 Speaker 1: traditional active funds do not do. Oh and by the way, 73 00:03:44,000 --> 00:03:46,360 Speaker 1: we recorded this while I was on vacation, which is 74 00:03:46,440 --> 00:03:48,280 Speaker 1: why you'll have to understand that I was calling from 75 00:03:48,320 --> 00:03:58,080 Speaker 1: the phone this time on Trilliance. Kathy would of our convestments. Kathy, 76 00:03:58,200 --> 00:04:00,960 Speaker 1: thanks for joining us on Trilliance. Happy to be here, Joel. 77 00:04:01,520 --> 00:04:03,880 Speaker 1: So when you think about what you do, how do 78 00:04:04,000 --> 00:04:08,520 Speaker 1: you describe it to your friends and family. Yes, we 79 00:04:08,600 --> 00:04:14,440 Speaker 1: are investors, asset managers focused exclusively on disruptive innovation, nothing else. 80 00:04:14,920 --> 00:04:18,720 Speaker 1: And these disruptive innovations are technologically enabled. They're going to 81 00:04:18,800 --> 00:04:21,640 Speaker 1: transform the way the world works and really make it 82 00:04:21,680 --> 00:04:26,120 Speaker 1: a better place. And why do you use E t F. Well, 83 00:04:26,240 --> 00:04:28,800 Speaker 1: I started with E t f s because as we 84 00:04:28,960 --> 00:04:33,920 Speaker 1: were studying thematically UH, the aftermath of the O eight 85 00:04:34,040 --> 00:04:37,640 Speaker 1: oh night meltdown, we were trying to discern trends, and 86 00:04:37,720 --> 00:04:40,720 Speaker 1: what we were seeing was an accelerated trend towards E 87 00:04:40,920 --> 00:04:45,240 Speaker 1: t f s taking market share. This usually happens, UH 88 00:04:45,600 --> 00:04:51,080 Speaker 1: in any disruptive innovation. The cheaper, better, faster winds and 89 00:04:51,400 --> 00:04:56,120 Speaker 1: gains increased traction throughout a very turbulent period. This was 90 00:04:56,240 --> 00:04:58,400 Speaker 1: holding true with E t S and I thought, well, 91 00:04:58,640 --> 00:05:02,320 Speaker 1: while the rappers terrific, it solves so many problems for 92 00:05:02,400 --> 00:05:07,000 Speaker 1: the end investor, why can't we do active in in 93 00:05:07,320 --> 00:05:11,640 Speaker 1: an E t F uh? And the answer was there's 94 00:05:12,080 --> 00:05:15,200 Speaker 1: no reason you cannot if you're willing to disclose your 95 00:05:15,240 --> 00:05:18,240 Speaker 1: holdings at the end of every day. UM, I want 96 00:05:18,279 --> 00:05:21,000 Speaker 1: to go back to the innovation and these broader themes. 97 00:05:21,680 --> 00:05:24,800 Speaker 1: Black Rock just had a press conference talking about mega 98 00:05:24,880 --> 00:05:26,960 Speaker 1: trends and it kind of sounded like what you've been 99 00:05:26,960 --> 00:05:28,600 Speaker 1: talking about for a while. And I want to bring 100 00:05:28,640 --> 00:05:32,400 Speaker 1: in Rachel because Rachel has been covering thematic investing heavily 101 00:05:32,560 --> 00:05:34,600 Speaker 1: and she met you a while ago and just set 102 00:05:34,680 --> 00:05:37,040 Speaker 1: us up on this whole idea of thematic investing in 103 00:05:37,440 --> 00:05:40,279 Speaker 1: your experience with Kathy. Yeah, so I first met Kathy 104 00:05:40,400 --> 00:05:43,280 Speaker 1: back in I think it was October, so it's been 105 00:05:43,279 --> 00:05:46,880 Speaker 1: a while now. She set up her funds back in fourteen, 106 00:05:46,920 --> 00:05:48,760 Speaker 1: so they've been running for about a year at that stage. 107 00:05:49,000 --> 00:05:51,040 Speaker 1: And my interest was piqued because I heard down the 108 00:05:51,080 --> 00:05:53,600 Speaker 1: grape vine that Kathy was using these e t f 109 00:05:53,680 --> 00:05:57,200 Speaker 1: s to actually invest in disruptive industries, but also bitcoin, 110 00:05:57,480 --> 00:05:59,360 Speaker 1: which got my attention at the time because I was 111 00:05:59,400 --> 00:06:01,440 Speaker 1: writing about orencies and I thought, hang on a second, 112 00:06:01,520 --> 00:06:03,840 Speaker 1: here's a way we can write about something really interesting 113 00:06:03,920 --> 00:06:06,200 Speaker 1: without staying too far from my beat. And I went 114 00:06:06,279 --> 00:06:08,080 Speaker 1: in to meet Kathy and learn a bit more about it, 115 00:06:08,160 --> 00:06:10,440 Speaker 1: and I was really blown away, really but how kind 116 00:06:10,440 --> 00:06:13,240 Speaker 1: of sort of sophisticated that the strategy was at the time. 117 00:06:13,760 --> 00:06:15,440 Speaker 1: Not only was it kind of bitcoin, it wasn't just 118 00:06:15,520 --> 00:06:17,800 Speaker 1: crypto focused. It was actually kind of looking at anything 119 00:06:17,839 --> 00:06:20,440 Speaker 1: that was disrupting things that were different kind of threads 120 00:06:20,480 --> 00:06:23,880 Speaker 1: of investment, looking at blockchain, different threads, looking at genomics. 121 00:06:24,120 --> 00:06:26,960 Speaker 1: It all seemed very kind of like futuristic and new wave, 122 00:06:27,240 --> 00:06:29,120 Speaker 1: and I found it was so interesting that I kept 123 00:06:29,160 --> 00:06:31,200 Speaker 1: kind of like following the progression of these funds and 124 00:06:31,240 --> 00:06:33,520 Speaker 1: then actually ended up writing a story all about kind 125 00:06:33,520 --> 00:06:35,640 Speaker 1: of Kathy and that the success of her her business 126 00:06:35,720 --> 00:06:39,040 Speaker 1: last year until Kathy, take us back. You started the et, 127 00:06:39,279 --> 00:06:42,440 Speaker 1: but you were doing themes back at your previous job. 128 00:06:43,279 --> 00:06:45,360 Speaker 1: What turned you onto themes and and why do you 129 00:06:45,440 --> 00:06:49,840 Speaker 1: ultimately go out in your own well A couple of reasons. 130 00:06:50,000 --> 00:06:54,880 Speaker 1: I was turned onto themes, specifically technologically enabled innovation, which 131 00:06:54,960 --> 00:06:59,480 Speaker 1: is which which impacts every sector of these days. When 132 00:06:59,560 --> 00:07:03,080 Speaker 1: I was started in the business, I started in economics, 133 00:07:03,600 --> 00:07:06,000 Speaker 1: but I knew very quickly I wanted to become an 134 00:07:06,040 --> 00:07:10,720 Speaker 1: analyst and then ultimately a portfolio manager. And at Jennison Associates, 135 00:07:11,000 --> 00:07:15,680 Speaker 1: great firm, wonderful mentors, six Agallis. He said, fine, you 136 00:07:15,760 --> 00:07:17,560 Speaker 1: can do that here, but you're gonna have to find 137 00:07:17,600 --> 00:07:21,600 Speaker 1: your own universe. And the analysts there were lifers. They 138 00:07:21,640 --> 00:07:25,760 Speaker 1: weren't going anywhere, so I had to just wait around for, 139 00:07:26,560 --> 00:07:28,600 Speaker 1: you know, new names to show up that kind of 140 00:07:28,720 --> 00:07:33,400 Speaker 1: fell through the cracks, like database publishing, Reuter's tele rate. 141 00:07:33,480 --> 00:07:36,840 Speaker 1: We called it database publishing at the time. Nobody wanted 142 00:07:36,880 --> 00:07:42,160 Speaker 1: to follow that. It didn't belong in either publishing or technology. 143 00:07:42,320 --> 00:07:44,760 Speaker 1: It was a fall through the crack stock, and so 144 00:07:45,160 --> 00:07:48,920 Speaker 1: I said, I want to follow that. This sounds really interesting. 145 00:07:48,960 --> 00:07:51,400 Speaker 1: And of course it was the precursor to the Internet. 146 00:07:52,040 --> 00:07:57,560 Speaker 1: So very often when ideas are discarded or you know, 147 00:07:58,160 --> 00:08:03,040 Speaker 1: dismissed uh leetly as ridiculous. Uh, there there can be 148 00:08:03,280 --> 00:08:07,320 Speaker 1: often something very interesting lurking there. It may not show 149 00:08:07,440 --> 00:08:11,720 Speaker 1: up right away, but sometimes the ideas that are dismissed 150 00:08:11,760 --> 00:08:16,040 Speaker 1: out of hand become the most important investment opportunities. We're 151 00:08:16,040 --> 00:08:18,120 Speaker 1: going to see internet being one of them. I'm thinking 152 00:08:18,240 --> 00:08:22,000 Speaker 1: of Xerox and the PC. Yes, that was another one. 153 00:08:22,760 --> 00:08:25,400 Speaker 1: But yeah, and so you started getting into these and 154 00:08:25,480 --> 00:08:28,679 Speaker 1: then you were a portfolio manager. Yes, and our Lions 155 00:08:28,720 --> 00:08:31,400 Speaker 1: Bernstein I headed up. I was c i O of 156 00:08:31,520 --> 00:08:36,880 Speaker 1: the Global Thematic Strategies and I joined during the tech 157 00:08:36,960 --> 00:08:41,719 Speaker 1: and telecom bust. Uh so uh it was at that 158 00:08:41,880 --> 00:08:45,240 Speaker 1: time we were just focused on disruption. Uh. And in 159 00:08:45,320 --> 00:08:47,960 Speaker 1: that case, it was the bust, and we were trying 160 00:08:48,000 --> 00:08:50,319 Speaker 1: to figure out, okay, what are the ramifications of the 161 00:08:50,440 --> 00:08:54,240 Speaker 1: bust and how is this going to change technology? And 162 00:08:54,360 --> 00:08:56,319 Speaker 1: one of the one of the articles that came out 163 00:08:56,360 --> 00:09:00,760 Speaker 1: at the time was I t it doesn't matter. It 164 00:09:00,920 --> 00:09:03,360 Speaker 1: was a Harvard Business Review. We were trying to get 165 00:09:03,360 --> 00:09:05,840 Speaker 1: our head around this. Remember we had the market had 166 00:09:05,880 --> 00:09:08,600 Speaker 1: gone wild on technology, and here was here was an 167 00:09:08,720 --> 00:09:12,040 Speaker 1: article in HBr saying it doesn't matter. And that was 168 00:09:12,679 --> 00:09:16,840 Speaker 1: that was, uh, you know, a precursor or a foreshadowing 169 00:09:17,080 --> 00:09:22,080 Speaker 1: of Amazon Web Services, the cloud. And so again, most 170 00:09:22,160 --> 00:09:24,839 Speaker 1: people were buying the dip even in oh one when 171 00:09:24,920 --> 00:09:28,880 Speaker 1: I was when I started, and we already were onto 172 00:09:28,920 --> 00:09:31,560 Speaker 1: the next thing. Wait a minute, there's a disruption here, 173 00:09:32,320 --> 00:09:36,320 Speaker 1: what could this possibly mean? So um, we did everything 174 00:09:36,400 --> 00:09:39,040 Speaker 1: we did was around disruption. But because a lot of 175 00:09:39,160 --> 00:09:42,679 Speaker 1: technologies were not ready, you know they were they were 176 00:09:42,800 --> 00:09:46,000 Speaker 1: birthed too many of them during the Internet bubble or 177 00:09:46,040 --> 00:09:48,760 Speaker 1: even way before, but they needed time to just hate. 178 00:09:49,240 --> 00:09:53,120 Speaker 1: So we we were focused on other disruptions, and one 179 00:09:53,200 --> 00:09:57,040 Speaker 1: of them was, Okay, investors have been disrupted. The tech 180 00:09:57,080 --> 00:10:01,480 Speaker 1: and telecom bust has turned people off. Stock interest rates 181 00:10:01,520 --> 00:10:05,360 Speaker 1: are only six percent long rates, so nobody's going to 182 00:10:05,440 --> 00:10:08,680 Speaker 1: want bonds. That of course was wrong. Uh, where else 183 00:10:08,720 --> 00:10:10,880 Speaker 1: are they going? And then we moved into housing as 184 00:10:10,880 --> 00:10:13,000 Speaker 1: a new asset class. Just to give you a sense 185 00:10:13,080 --> 00:10:16,480 Speaker 1: of how we were looking at disruption at the time now, 186 00:10:17,000 --> 00:10:20,960 Speaker 1: the technologies are ready for prime time. They were they've 187 00:10:20,960 --> 00:10:23,560 Speaker 1: been jest stating these last twenty years, and we are 188 00:10:23,640 --> 00:10:27,680 Speaker 1: hitting tipping points now where demand demand for electric vehicles 189 00:10:27,720 --> 00:10:29,840 Speaker 1: we think will go up twenty fold during the next 190 00:10:30,040 --> 00:10:33,600 Speaker 1: UH during the next five six years, demand for DNA 191 00:10:33,720 --> 00:10:37,920 Speaker 1: sequencing is going to go up fortyfold. These are unit 192 00:10:37,960 --> 00:10:41,360 Speaker 1: growth numbers because costs are moving down so rapidly, and 193 00:10:41,480 --> 00:10:46,920 Speaker 1: I don't think economists or analysts or portfolio managers are 194 00:10:47,080 --> 00:10:49,760 Speaker 1: ready for this right now. I don't think research departments 195 00:10:49,800 --> 00:10:52,760 Speaker 1: are ready for this. They have to restructure because every 196 00:10:52,840 --> 00:10:55,640 Speaker 1: analyst is going to have to become very conversant and 197 00:10:55,760 --> 00:11:00,640 Speaker 1: comfortable with technology. And we're focused on five technology platforms 198 00:11:00,720 --> 00:11:04,960 Speaker 1: or innovation platforms. Not only is technology seeping into every sector, 199 00:11:05,080 --> 00:11:08,040 Speaker 1: blurring sector lines, which I know is important in ETFs, 200 00:11:08,520 --> 00:11:14,080 Speaker 1: but these three innovation platforms, they are converging. So analysts 201 00:11:14,240 --> 00:11:18,400 Speaker 1: broke their responsibilities broken out by very specialized segments of 202 00:11:18,480 --> 00:11:22,920 Speaker 1: sectors are not going to be able to analyze these 203 00:11:22,960 --> 00:11:27,760 Speaker 1: innovations correctly without again a restructuring of their responsibilities. So 204 00:11:27,880 --> 00:11:32,040 Speaker 1: what are these five platforms that you've divided and are 205 00:11:32,160 --> 00:11:35,160 Speaker 1: using to sort of organize your university. Yes, and these 206 00:11:35,200 --> 00:11:38,360 Speaker 1: would be in Silicon Valley. They would be considered general 207 00:11:38,440 --> 00:11:44,640 Speaker 1: purpose technology platforms. Uh there there there. We didn't choose these, um, 208 00:11:45,120 --> 00:11:48,160 Speaker 1: but they're at All of these are at tipping points 209 00:11:48,240 --> 00:11:50,800 Speaker 1: in terms of adoption. And I can tell you how 210 00:11:50,880 --> 00:11:53,800 Speaker 1: we get to tipping points, but they are DNA sequencing. 211 00:11:54,840 --> 00:11:58,760 Speaker 1: The tipping points always happen because costs are collapsing, and 212 00:11:58,840 --> 00:12:03,319 Speaker 1: they're collapsing there so that we believe that the number 213 00:12:03,360 --> 00:12:07,120 Speaker 1: of whole human genomes sequenced, which was two point four 214 00:12:07,200 --> 00:12:10,719 Speaker 1: million last year, that's half of all the genomes ever 215 00:12:10,880 --> 00:12:13,719 Speaker 1: sequenced in the world ever that happened just last year. 216 00:12:14,000 --> 00:12:16,240 Speaker 1: We think that's going to a hundred million in five years. 217 00:12:16,880 --> 00:12:19,600 Speaker 1: Uh and we're and we think it's going ultimately into billions. 218 00:12:19,679 --> 00:12:22,240 Speaker 1: And it's because costs are collapsing here. And we will 219 00:12:22,280 --> 00:12:26,600 Speaker 1: get our genome sequenced every every every year, every other 220 00:12:26,720 --> 00:12:29,400 Speaker 1: year to figure out what's mutating in our bodies so 221 00:12:29,600 --> 00:12:32,679 Speaker 1: we can catch cancer in stage one and then we 222 00:12:32,800 --> 00:12:35,760 Speaker 1: can edit it out with gene editing. So that's one 223 00:12:35,880 --> 00:12:39,360 Speaker 1: huge platform that's an e t F A r KG right, 224 00:12:39,440 --> 00:12:44,000 Speaker 1: the genomic revolution on that one that does and it's 225 00:12:44,080 --> 00:12:47,199 Speaker 1: unusual for US to have a fund that looks like 226 00:12:47,320 --> 00:12:52,319 Speaker 1: a healthcare sector fund, but it is a slice of healthcare. 227 00:12:52,440 --> 00:12:56,040 Speaker 1: It is futuristic healthcare if you look at it. Uh, 228 00:12:56,720 --> 00:13:03,079 Speaker 1: it includes DNA sequencing, molecular diagnostic testing companies, cart technology companies, 229 00:13:03,120 --> 00:13:08,240 Speaker 1: so with immunotherapy, crisper, gene editing, other kinds of gene therapy. 230 00:13:09,040 --> 00:13:14,040 Speaker 1: So again, our funds are very forward looking. You'll find 231 00:13:14,160 --> 00:13:16,800 Speaker 1: many sector funds are where they are because of what 232 00:13:16,920 --> 00:13:20,200 Speaker 1: has happened historically. That's true of any index. Our funds 233 00:13:20,280 --> 00:13:25,679 Speaker 1: tend to be very active relative to you know, their counterparts, 234 00:13:25,800 --> 00:13:28,720 Speaker 1: if there are any in the market, because most counterparts, 235 00:13:28,800 --> 00:13:32,280 Speaker 1: even if they call themselves innovation, are based on some index. 236 00:13:32,440 --> 00:13:35,320 Speaker 1: That's the screen. Our screen is not an index. Our 237 00:13:35,360 --> 00:13:40,800 Speaker 1: screen is our research. So very different. So DNA sequencing, UH, 238 00:13:41,200 --> 00:13:46,840 Speaker 1: robotics with collaborative robots, the cost or collapsing here, energy storage, 239 00:13:46,880 --> 00:13:51,480 Speaker 1: so electric vehicles, UH, elon musk leading the charge, so 240 00:13:51,640 --> 00:13:56,440 Speaker 1: to speak. Artificial intelligence is really part of the next 241 00:13:56,520 --> 00:14:01,000 Speaker 1: generation Internet. It's it's going to turbocharge the Internet, the 242 00:14:01,120 --> 00:14:04,920 Speaker 1: cloud if you'd like. UH, and it's it's ready for 243 00:14:05,000 --> 00:14:10,120 Speaker 1: prime time because uh, we've pulled human programmers largely out 244 00:14:10,160 --> 00:14:13,280 Speaker 1: of the equation, and then finally blockchain technology, which is 245 00:14:13,320 --> 00:14:16,800 Speaker 1: also part of the next generation Internet. Yeah, and I 246 00:14:16,920 --> 00:14:18,959 Speaker 1: find this really kind of fascinating because when you look 247 00:14:18,960 --> 00:14:21,520 Speaker 1: at what's happened since Kathy set up her funds back 248 00:14:21,560 --> 00:14:25,640 Speaker 1: in you've really seen a proliferation of these types of 249 00:14:25,680 --> 00:14:28,280 Speaker 1: strategies coming through in the E T F industry, But 250 00:14:28,440 --> 00:14:30,760 Speaker 1: most of these are passive. If you look at kind 251 00:14:30,760 --> 00:14:33,800 Speaker 1: of the proportion of passive to active around the numbers, 252 00:14:33,800 --> 00:14:36,400 Speaker 1: and I think it's only eleven percent that are actively managed, 253 00:14:36,440 --> 00:14:39,080 Speaker 1: and significant number of those are run by Kathy. So 254 00:14:39,160 --> 00:14:40,960 Speaker 1: it's quite interesting to me that this is a very 255 00:14:41,000 --> 00:14:43,840 Speaker 1: different approach because inherently it makes quite a lot of 256 00:14:43,920 --> 00:14:46,600 Speaker 1: sense when you're thinking about sort of you know, futuristic 257 00:14:46,680 --> 00:14:49,040 Speaker 1: looking industries to try and think about something where you're 258 00:14:49,080 --> 00:14:52,560 Speaker 1: not necessarily pinned down to indexes that that can only 259 00:14:52,640 --> 00:14:56,040 Speaker 1: really rebalance on a twice annual or annual kind of basis. 260 00:14:56,160 --> 00:14:57,840 Speaker 1: So I find that kind of like, sort of very 261 00:14:57,840 --> 00:14:59,920 Speaker 1: interesting about this this approach that a lot of our 262 00:15:00,080 --> 00:15:02,080 Speaker 1: people have kind of followed it, but they've chosen to 263 00:15:02,160 --> 00:15:04,720 Speaker 1: go to the passive, whereas Kathy has has has the 264 00:15:04,840 --> 00:15:07,960 Speaker 1: active kind of DNA as well. Thank you. Can I 265 00:15:08,080 --> 00:15:10,120 Speaker 1: just add one thing to that, and thank you Rachel 266 00:15:10,160 --> 00:15:12,440 Speaker 1: for saying that. Um. One of the other things. The 267 00:15:12,560 --> 00:15:16,880 Speaker 1: other benefits of active management is we trade around our 268 00:15:16,960 --> 00:15:22,640 Speaker 1: names aggressively because disruptive innovation is inherently controversial and I 269 00:15:23,320 --> 00:15:26,720 Speaker 1: we just lie there and wait. We know that Tesla 270 00:15:27,160 --> 00:15:28,960 Speaker 1: when it was in the three eighties, we knew it 271 00:15:29,040 --> 00:15:30,960 Speaker 1: was going to come down. We sold up there. Even 272 00:15:31,000 --> 00:15:34,040 Speaker 1: though our price target is as high as it is. 273 00:15:34,560 --> 00:15:37,040 Speaker 1: We knew we were going to get opportunities. It never 274 00:15:37,280 --> 00:15:40,360 Speaker 1: left the top position in the fund, but instead of 275 00:15:40,480 --> 00:15:43,720 Speaker 1: being at twelve or thirteen percent, we took it down 276 00:15:43,800 --> 00:15:48,680 Speaker 1: to eight percent. If you just isolate the trading activity 277 00:15:48,840 --> 00:15:50,960 Speaker 1: in Tesla alone, and we do this with all of 278 00:15:51,000 --> 00:15:54,320 Speaker 1: our names last year, and we had a number of 279 00:15:54,440 --> 00:15:59,080 Speaker 1: round trips. If you just isolate that trading alone, the 280 00:15:59,160 --> 00:16:01,440 Speaker 1: stock itself off was up six and a half percent 281 00:16:01,600 --> 00:16:05,080 Speaker 1: last year, but the our trading activity alone added another 282 00:16:05,240 --> 00:16:09,080 Speaker 1: hundred and seventy five basis points to our performance last year, 283 00:16:09,200 --> 00:16:11,600 Speaker 1: just that one stock, and we do that with every 284 00:16:11,640 --> 00:16:14,640 Speaker 1: stock now. It is true Tesla is probably one of 285 00:16:14,720 --> 00:16:18,080 Speaker 1: the most volatile and most controversial, so we have a 286 00:16:18,120 --> 00:16:20,640 Speaker 1: lot of opportunities, but that is one of the benefits 287 00:16:20,680 --> 00:16:23,000 Speaker 1: of active management. And I think before you though, when 288 00:16:23,080 --> 00:16:24,520 Speaker 1: when I met you, I was I met you at 289 00:16:24,520 --> 00:16:27,080 Speaker 1: a conference somewhere downtown, like the Millennial Hotel or something, 290 00:16:27,160 --> 00:16:29,560 Speaker 1: and when you talked about these, I said, I don't 291 00:16:29,560 --> 00:16:31,800 Speaker 1: think it's going to go that well. I said, you know, 292 00:16:32,240 --> 00:16:34,320 Speaker 1: I don't know why she doesn't do him passive, because 293 00:16:34,480 --> 00:16:36,320 Speaker 1: that's just what everybody wants right now. The fact that 294 00:16:36,360 --> 00:16:37,920 Speaker 1: you made him active at the time, I thought, man, 295 00:16:38,040 --> 00:16:41,760 Speaker 1: that that could sink these just because people want stuff 296 00:16:41,840 --> 00:16:43,920 Speaker 1: cheap and passive. Yours are a little on the price 297 00:16:44,000 --> 00:16:46,920 Speaker 1: your side and they're active. Um, but you've defied the 298 00:16:46,960 --> 00:16:50,320 Speaker 1: odds active equity mutual funds have seen. I don't know 299 00:16:50,320 --> 00:16:52,160 Speaker 1: what the number is, it's probably close to a trillion 300 00:16:52,200 --> 00:16:55,560 Speaker 1: dollars and outflows since you launched. You've taken in two 301 00:16:55,640 --> 00:16:58,400 Speaker 1: point five billion in the past three years, so you've 302 00:16:58,440 --> 00:17:02,440 Speaker 1: completely bucked the trend. Talk about that why you had 303 00:17:02,480 --> 00:17:04,359 Speaker 1: to go active. Was it just because you couldn't be 304 00:17:04,480 --> 00:17:08,000 Speaker 1: locked into anything, You had to have that freedom. Yes, 305 00:17:08,320 --> 00:17:11,840 Speaker 1: So the number you quoted there are e t f s, 306 00:17:11,920 --> 00:17:15,000 Speaker 1: they're they're close to three billion now, but we we 307 00:17:15,600 --> 00:17:18,399 Speaker 1: had to do something else. And I'll explain why we 308 00:17:18,560 --> 00:17:21,560 Speaker 1: had to pivot, because I funded the company for the 309 00:17:21,640 --> 00:17:25,399 Speaker 1: first three years and what you said that Eric was 310 00:17:25,640 --> 00:17:30,080 Speaker 1: actually happening. I the network I had in the financial community. 311 00:17:30,160 --> 00:17:32,920 Speaker 1: And remember I've been around a long time in this 312 00:17:33,119 --> 00:17:36,920 Speaker 1: business and I do have a very wonderful network. My 313 00:17:37,080 --> 00:17:40,240 Speaker 1: network was nowhere to be found on the passive. On 314 00:17:40,320 --> 00:17:42,520 Speaker 1: the passive side, on the e t F side, I 315 00:17:42,680 --> 00:17:46,439 Speaker 1: was shocked that most people I was talking to did 316 00:17:46,560 --> 00:17:50,920 Speaker 1: not understand what active management was. They just didn't understand it. 317 00:17:51,680 --> 00:17:55,199 Speaker 1: And so we had to We had to start um 318 00:17:56,000 --> 00:17:59,040 Speaker 1: using other rappers because while we were being asked, would 319 00:17:59,040 --> 00:18:01,200 Speaker 1: we do it? And that's what you do as a 320 00:18:01,240 --> 00:18:03,399 Speaker 1: small business. We are now up to nine and a 321 00:18:03,440 --> 00:18:09,120 Speaker 1: half billion dollars all active, but any rapper. We've got 322 00:18:09,200 --> 00:18:13,200 Speaker 1: two distributors. You know. We subadvised for mutual funds throughout Asia, 323 00:18:13,240 --> 00:18:16,720 Speaker 1: pack UH and e t f s of course here 324 00:18:17,160 --> 00:18:21,159 Speaker 1: mostly in the United States, but interestingly, sovereign wealth funds 325 00:18:21,480 --> 00:18:24,239 Speaker 1: in other parts other parts of the world have been 326 00:18:24,320 --> 00:18:26,880 Speaker 1: buying some of our et f s because they don't 327 00:18:26,920 --> 00:18:29,159 Speaker 1: have to go through all of the due diligence that 328 00:18:29,840 --> 00:18:33,080 Speaker 1: you know, a traditional separately managed account would go through. 329 00:18:33,119 --> 00:18:36,359 Speaker 1: We also have separately managed accounts. I went to the 330 00:18:36,440 --> 00:18:40,920 Speaker 1: Morning Star conference in October of thirteen, and this was 331 00:18:41,119 --> 00:18:44,119 Speaker 1: right before we started the company, and on stage was 332 00:18:44,240 --> 00:18:48,560 Speaker 1: Eugene Fama being interviewed a fireside chat, and he said 333 00:18:48,640 --> 00:18:53,480 Speaker 1: at that conference, he said, active management is dead, it 334 00:18:53,760 --> 00:18:57,159 Speaker 1: is disappearing. And you know this was there might have 335 00:18:57,200 --> 00:18:59,560 Speaker 1: been two thousand people in the room, and everybody was cheering, 336 00:18:59,640 --> 00:19:03,000 Speaker 1: and and I looked around. I really understood at that moment, 337 00:19:03,240 --> 00:19:06,520 Speaker 1: Oh my goodness, I'm the only active manager here. This 338 00:19:06,760 --> 00:19:10,280 Speaker 1: is crazy. I would have thought, you know, doesn't everybody 339 00:19:10,359 --> 00:19:12,560 Speaker 1: want to know about this wrapper, which is so good 340 00:19:12,720 --> 00:19:18,600 Speaker 1: and so interesting. Um, So we went to active when 341 00:19:18,640 --> 00:19:22,639 Speaker 1: it comes to innovation, it's the only way to manage money. Um. 342 00:19:22,880 --> 00:19:28,080 Speaker 1: To me, the idea of passive and innovation, well, that's 343 00:19:28,160 --> 00:19:33,600 Speaker 1: an oxymoron, right. And the screen for our research is 344 00:19:34,000 --> 00:19:38,000 Speaker 1: the screen for our portfolios is our research. We are 345 00:19:38,080 --> 00:19:42,639 Speaker 1: constructing autonomous vehicles. What is it? What goes into it? 346 00:19:42,760 --> 00:19:46,240 Speaker 1: We're doing first principles research and we're using something called 347 00:19:46,359 --> 00:19:50,320 Speaker 1: rights law in order to understand the learning curves which 348 00:19:50,400 --> 00:19:54,080 Speaker 1: caused cost declines in these new technologies, and then we 349 00:19:54,320 --> 00:19:57,320 Speaker 1: use price elasticity of demands, so there's a lot of 350 00:19:57,440 --> 00:20:00,720 Speaker 1: top down you know, how big is this market going 351 00:20:00,800 --> 00:20:04,160 Speaker 1: to be? If you don't have perspective when you're investing 352 00:20:04,240 --> 00:20:09,040 Speaker 1: in innovation, you don't have the courage of conviction. Um, 353 00:20:09,280 --> 00:20:12,080 Speaker 1: now you came out and you just basically hit a 354 00:20:12,119 --> 00:20:14,040 Speaker 1: home run right out of the gate. Your fund went 355 00:20:14,160 --> 00:20:17,080 Speaker 1: up like two or three times. The SMP five undered 356 00:20:17,080 --> 00:20:19,720 Speaker 1: I called the shiny object moment. I'm sure you've got 357 00:20:19,760 --> 00:20:21,760 Speaker 1: a lot of people just giving you looks because of that. 358 00:20:22,440 --> 00:20:24,040 Speaker 1: How much of the flows that have come in do 359 00:20:24,080 --> 00:20:27,119 Speaker 1: you think are just people who just saw this and 360 00:20:27,520 --> 00:20:31,800 Speaker 1: crazy performance and bought in versus you know, talk to 361 00:20:31,880 --> 00:20:35,479 Speaker 1: you believe in Cathy and are there for the long haul? Uh. 362 00:20:35,640 --> 00:20:39,720 Speaker 1: In the beginning, it's interesting Rachel mentioned bitcoin. Most people 363 00:20:39,840 --> 00:20:43,399 Speaker 1: dismissed us because it was bitcoin. So in in in 364 00:20:43,560 --> 00:20:45,760 Speaker 1: eighty seven alone we were up eighty seven and a 365 00:20:45,800 --> 00:20:48,159 Speaker 1: half percent. But if you had put if you had 366 00:20:48,200 --> 00:20:51,200 Speaker 1: just left our bitcoin in cash, which we wouldn't do 367 00:20:51,280 --> 00:20:55,120 Speaker 1: of course, so a conservative way of calculating non bit 368 00:20:55,240 --> 00:20:58,520 Speaker 1: poorn bitcoin performance, we would have been up a low 369 00:20:58,640 --> 00:21:01,320 Speaker 1: sixties percent, so I was more than double the market. 370 00:21:02,000 --> 00:21:04,800 Speaker 1: Uh No. In the beginning, we got oh, they're using 371 00:21:04,920 --> 00:21:08,120 Speaker 1: bitcoin as a as a gimmick for from from from 372 00:21:08,280 --> 00:21:10,919 Speaker 1: some journalists in the et F space that I respect 373 00:21:11,000 --> 00:21:14,399 Speaker 1: and like not a lot. I thought, Wow, they didn't 374 00:21:14,400 --> 00:21:16,800 Speaker 1: read our white papers. We've done so much work on this, 375 00:21:17,359 --> 00:21:20,680 Speaker 1: so there was an automatic dismissal as this is a gimmick. 376 00:21:21,280 --> 00:21:23,720 Speaker 1: And we also have had that. We've had that a 377 00:21:23,760 --> 00:21:26,159 Speaker 1: little bit with Tesla as well. You know, you're just 378 00:21:26,359 --> 00:21:28,240 Speaker 1: you just want to get out there, and and and 379 00:21:28,960 --> 00:21:32,240 Speaker 1: and if they only saw the research that we put 380 00:21:32,280 --> 00:21:35,600 Speaker 1: into this. So we've had a great social media and 381 00:21:35,840 --> 00:21:40,359 Speaker 1: marketing presence and this has been building slowly. But I 382 00:21:40,480 --> 00:21:43,200 Speaker 1: think the main thing has been slowly it's demand pull. 383 00:21:43,720 --> 00:21:46,280 Speaker 1: The wirehouses were slow to put us on where we're 384 00:21:46,359 --> 00:21:47,960 Speaker 1: on a few now, we have a few more to go. 385 00:21:49,000 --> 00:21:53,920 Speaker 1: But it's been demand pulled because investors, whether they see 386 00:21:54,000 --> 00:21:57,399 Speaker 1: us on social media or on other media, they know 387 00:21:57,960 --> 00:22:02,480 Speaker 1: we are right. They know because they feel technology changing 388 00:22:02,560 --> 00:22:05,640 Speaker 1: their own line lives so quickly, or their children's lives 389 00:22:05,720 --> 00:22:08,840 Speaker 1: or their grandchildren's lives, and they know they're missing it 390 00:22:09,040 --> 00:22:12,120 Speaker 1: in their portfolios. They they do not have a piece 391 00:22:12,160 --> 00:22:15,159 Speaker 1: of the action, and they want to you know, they 392 00:22:15,240 --> 00:22:19,480 Speaker 1: would like to ride, whether it's five of their portfolio. 393 00:22:19,960 --> 00:22:22,240 Speaker 1: The other thing that I think we've done pretty well 394 00:22:22,359 --> 00:22:26,280 Speaker 1: is helped people understand that traditional indexes are filling up 395 00:22:26,320 --> 00:22:29,760 Speaker 1: with value traps because of this innovation, So why not 396 00:22:30,040 --> 00:22:32,880 Speaker 1: use us as a hedge. Even if you're completely passive, 397 00:22:33,600 --> 00:22:36,199 Speaker 1: you're you're you have value traps building up in your 398 00:22:36,280 --> 00:22:39,879 Speaker 1: value portfolios and in your growth portfolios. That's how fast 399 00:22:40,040 --> 00:22:42,760 Speaker 1: innovation is evolving. Who would you say, are are you 400 00:22:42,880 --> 00:22:44,760 Speaker 1: bias for for the E T s? Is it primarily 401 00:22:44,800 --> 00:22:48,160 Speaker 1: an institutional marketplace, or are you getting your funds into 402 00:22:48,240 --> 00:22:53,120 Speaker 1: financial advisors or even direct to retail? Uh it's financial 403 00:22:53,200 --> 00:22:58,600 Speaker 1: advisors direct to retail. For sure. We're seeing increasing institutional interest, 404 00:22:59,760 --> 00:23:04,359 Speaker 1: but that's more funds outside the rest of the world. 405 00:23:04,440 --> 00:23:07,320 Speaker 1: Who will you know, get a taste of innovation through 406 00:23:07,359 --> 00:23:09,639 Speaker 1: our E t f s and then perhaps invite us 407 00:23:09,680 --> 00:23:13,919 Speaker 1: into pitch for an s m A a separately managed account. Uh. 408 00:23:14,560 --> 00:23:18,760 Speaker 1: But what happened in March of two thousand sixteen, UH 409 00:23:19,000 --> 00:23:23,159 Speaker 1: is we got our first institutional account, a large state 410 00:23:23,400 --> 00:23:27,960 Speaker 1: employee retirement system in the Midwest who was my client 411 00:23:28,800 --> 00:23:33,159 Speaker 1: at my former firm, and uh, they found us. We 412 00:23:33,359 --> 00:23:36,040 Speaker 1: had tried to find them, but their gatekeepers wouldn't let 413 00:23:36,119 --> 00:23:38,720 Speaker 1: us in. And then they had a young analyst who 414 00:23:38,960 --> 00:23:41,679 Speaker 1: was charged with finding out what's going on in innovation. 415 00:23:42,520 --> 00:23:46,920 Speaker 1: He contacted us and after five months we realized, oh, 416 00:23:47,800 --> 00:23:51,160 Speaker 1: I know your boss, I know you know. And so anyway, 417 00:23:51,560 --> 00:23:54,400 Speaker 1: they gave us two hundred million dollars when we only 418 00:23:54,440 --> 00:23:59,720 Speaker 1: had twenty million dollars. And so in March nineteen we 419 00:23:59,840 --> 00:24:02,640 Speaker 1: have our three year record. Now we're making a big 420 00:24:02,920 --> 00:24:07,639 Speaker 1: institutional push. And so whether again we're rapper agnostic. Now, 421 00:24:08,040 --> 00:24:10,639 Speaker 1: if an institution wants to use et F s, fantastic, 422 00:24:10,760 --> 00:24:14,600 Speaker 1: If separately managed accounts, whatever the reason, fine, uh sub 423 00:24:14,640 --> 00:24:24,439 Speaker 1: advising for mutual funds. So I think like have these experience, 424 00:24:24,520 --> 00:24:27,320 Speaker 1: like illustrate something that's very common for new issues in 425 00:24:27,359 --> 00:24:29,400 Speaker 1: the et F space as well. Though, it's just it's 426 00:24:29,480 --> 00:24:32,639 Speaker 1: very hard to get that institutional money, which is obviously 427 00:24:32,680 --> 00:24:34,960 Speaker 1: where the big bucks lie when you are small, and 428 00:24:35,040 --> 00:24:37,040 Speaker 1: you have to kind of like have the longevity to 429 00:24:37,080 --> 00:24:39,520 Speaker 1: get past that three year track record before you can 430 00:24:39,600 --> 00:24:43,320 Speaker 1: really pitch the decision makers that have those millions to spend. 431 00:24:43,640 --> 00:24:48,120 Speaker 1: Yes and it's been very interesting. Yeah, performance has been 432 00:24:48,280 --> 00:24:50,680 Speaker 1: very helpful. Thanks be to God. I always add that, 433 00:24:51,040 --> 00:24:54,399 Speaker 1: but I I will say, uh, you know, we for 434 00:24:54,640 --> 00:24:58,200 Speaker 1: a US based manager, more than half of our assets 435 00:24:58,359 --> 00:25:00,159 Speaker 1: are in the rest of the world. I think the 436 00:25:00,240 --> 00:25:05,440 Speaker 1: most important strategic decisions we made were to outsource distribution. 437 00:25:05,880 --> 00:25:08,560 Speaker 1: So Nico Asset Management our partner in the rest of 438 00:25:08,600 --> 00:25:11,960 Speaker 1: the world. They are scaling us through quickly because Asia 439 00:25:12,200 --> 00:25:17,400 Speaker 1: is hungry for innovation, particularly the kind of innovation we're researching. 440 00:25:17,440 --> 00:25:21,760 Speaker 1: They're hungry for our research. And uh, of course Resolute 441 00:25:21,800 --> 00:25:24,360 Speaker 1: Investment Managers in the United States is scaling us here. 442 00:25:24,760 --> 00:25:26,800 Speaker 1: So Kathy, one of the things that I'm really interested 443 00:25:26,840 --> 00:25:31,479 Speaker 1: in is this idea of your research. So walk us 444 00:25:31,560 --> 00:25:36,160 Speaker 1: through how you go about finding companies and then from 445 00:25:36,200 --> 00:25:41,720 Speaker 1: identifying them to allocating to them. Sure, well, it starts 446 00:25:41,760 --> 00:25:44,840 Speaker 1: with our research. So since I started on the autonomous 447 00:25:44,920 --> 00:25:50,359 Speaker 1: vehicle example, I'll keep going there. Uh. We charged our 448 00:25:50,400 --> 00:25:53,600 Speaker 1: analysts to figure out what was going to make an 449 00:25:53,640 --> 00:25:59,080 Speaker 1: autonomous vehicle work. And so our director of research, Brett 450 00:25:59,400 --> 00:26:03,520 Speaker 1: uh Intin is an M I T engineer by by training, 451 00:26:03,800 --> 00:26:06,000 Speaker 1: and he needs to break everything down and then build 452 00:26:06,040 --> 00:26:08,680 Speaker 1: it up and and has really guided our analysts to 453 00:26:08,720 --> 00:26:12,000 Speaker 1: do the same. So to give you an example, uh, 454 00:26:12,119 --> 00:26:17,200 Speaker 1: Tasha Kini comes into our brainstorming on a Friday. She's 455 00:26:17,240 --> 00:26:20,399 Speaker 1: been working on the autonomous model and and and our brainstorm. 456 00:26:20,480 --> 00:26:22,560 Speaker 1: You're welcome to it anytime you'd like to join. It's 457 00:26:22,640 --> 00:26:25,840 Speaker 1: from one to three and it's research driven. Our analysts 458 00:26:25,880 --> 00:26:29,840 Speaker 1: come in with the most interesting or controversial, provocative ideas 459 00:26:29,880 --> 00:26:31,879 Speaker 1: they've heard or the biggest breakthrough they've had in their 460 00:26:31,920 --> 00:26:35,359 Speaker 1: own research. This week, Tasha comes in and said, it 461 00:26:35,480 --> 00:26:38,800 Speaker 1: appears that the brains of an autonomous vehicle are going 462 00:26:38,880 --> 00:26:42,080 Speaker 1: to be GPUs. And I looked at her and I said, 463 00:26:42,119 --> 00:26:44,960 Speaker 1: this was two thousand fourteen. I said what I said 464 00:26:45,520 --> 00:26:49,399 Speaker 1: the Nvidia that that stock is being thrown out because 465 00:26:49,440 --> 00:26:52,000 Speaker 1: it's a PC proxy. M PCs are dropping at a 466 00:26:52,040 --> 00:26:54,639 Speaker 1: double digit rate. It was selling it, I think eleven 467 00:26:54,720 --> 00:26:57,879 Speaker 1: times earnings. And then James piped it. He was at 468 00:26:57,880 --> 00:27:00,760 Speaker 1: a video for nine years and he said, okay, well 469 00:27:00,840 --> 00:27:03,520 Speaker 1: that makes a lot of sense because autonomous vehicles are 470 00:27:03,680 --> 00:27:10,800 Speaker 1: artificial intelligence projects and GPUs have of of all of 471 00:27:11,000 --> 00:27:16,000 Speaker 1: the doer, of all the training and artificial intelligence. And 472 00:27:16,080 --> 00:27:20,000 Speaker 1: I said, James, nobody knows that no analyst out there 473 00:27:20,080 --> 00:27:23,200 Speaker 1: knows that I've been around a while. I know what 474 00:27:23,359 --> 00:27:26,160 Speaker 1: people think in video is. And so in video, which 475 00:27:26,200 --> 00:27:28,720 Speaker 1: was already in our portfolios for gaming, it was just 476 00:27:28,840 --> 00:27:31,359 Speaker 1: a small position, that was a one percent position. It 477 00:27:31,520 --> 00:27:34,600 Speaker 1: started moving up pretty and and you know, the trading 478 00:27:34,720 --> 00:27:36,840 Speaker 1: range that Tesla has been in for these last four 479 00:27:36,920 --> 00:27:39,840 Speaker 1: years in video was in the same kind of trading range. 480 00:27:39,880 --> 00:27:44,720 Speaker 1: While while computer PCs shipments were dropping. Every time it 481 00:27:44,800 --> 00:27:47,240 Speaker 1: dropped to the low end sort of that fourteen dollars, 482 00:27:47,680 --> 00:27:49,200 Speaker 1: we would pick it up, and when it got to 483 00:27:49,320 --> 00:27:52,399 Speaker 1: twenty dollars, we would sell some and then fourteen and twenty. 484 00:27:52,640 --> 00:27:54,439 Speaker 1: And what happens over time if you get a long 485 00:27:54,560 --> 00:27:57,320 Speaker 1: enough base, which I believe we have now in Tesla 486 00:27:58,400 --> 00:28:02,119 Speaker 1: and certainly did back then in in Vidia. UH, at 487 00:28:02,240 --> 00:28:04,320 Speaker 1: one point it's going to break out of that base 488 00:28:04,640 --> 00:28:11,040 Speaker 1: because a number of research analysts and then portfolio managers decide, hey, 489 00:28:11,160 --> 00:28:15,280 Speaker 1: we need some exposure to artificial intelligence and autonomous vehicles. 490 00:28:15,680 --> 00:28:17,880 Speaker 1: This became the go to. So it went from fourteen 491 00:28:17,960 --> 00:28:23,639 Speaker 1: dollars in two thousand fifteen UH to three hundred dollars 492 00:28:24,440 --> 00:28:27,320 Speaker 1: in two thousand eighteen. This is venture like in terms 493 00:28:27,400 --> 00:28:30,240 Speaker 1: of its returns, and we consider ourselves the closest you'll 494 00:28:30,240 --> 00:28:33,760 Speaker 1: find to a venture capital firm in the public equity market. 495 00:28:33,840 --> 00:28:37,760 Speaker 1: So some fourteen to three hundred, uh, it went from 496 00:28:37,800 --> 00:28:40,040 Speaker 1: one percent of our portfolios. While it was in that 497 00:28:40,160 --> 00:28:43,280 Speaker 1: fourteen to twenty range, we got it into it would 498 00:28:43,280 --> 00:28:45,240 Speaker 1: be in the top five, so that would have been 499 00:28:45,280 --> 00:28:48,800 Speaker 1: in the five to ten percent range, depending on the portfolio. 500 00:28:49,680 --> 00:28:51,800 Speaker 1: And as it got to that three hundred level, and 501 00:28:51,920 --> 00:28:55,120 Speaker 1: it no longer met our minimum hurdle rate of return, 502 00:28:55,200 --> 00:28:58,760 Speaker 1: which is a fifteen percent annualized rate of return over 503 00:28:58,920 --> 00:29:01,800 Speaker 1: five years, so that means of doubling every five years. 504 00:29:02,120 --> 00:29:05,400 Speaker 1: If we can't say to ourselves that this stock is 505 00:29:05,480 --> 00:29:08,080 Speaker 1: going to do that in the next five years, then 506 00:29:08,160 --> 00:29:10,160 Speaker 1: we say, even if it's a core position, we will 507 00:29:10,200 --> 00:29:12,600 Speaker 1: take it down to the bottom five. So it started 508 00:29:12,680 --> 00:29:16,080 Speaker 1: in the bottom five, got to the top five in 509 00:29:16,200 --> 00:29:21,200 Speaker 1: two thousand seventeen, and then by the time October rolled 510 00:29:21,200 --> 00:29:23,400 Speaker 1: around last year, when it was at three, was back 511 00:29:23,480 --> 00:29:26,000 Speaker 1: in the bottom five. And then as you know, it 512 00:29:26,160 --> 00:29:31,160 Speaker 1: dropped more than almost in one quarter and we and 513 00:29:31,320 --> 00:29:33,120 Speaker 1: we put it back into the top five because it 514 00:29:33,280 --> 00:29:35,760 Speaker 1: is going to be one of the biggest autonomous vehicle plays, 515 00:29:36,280 --> 00:29:39,000 Speaker 1: so so much of that was just identifying sort of 516 00:29:39,080 --> 00:29:43,280 Speaker 1: a special ingredient that was gonna you know that you 517 00:29:43,360 --> 00:29:46,520 Speaker 1: guys are just gonna like double down on. And I 518 00:29:46,560 --> 00:29:48,800 Speaker 1: guess what I'm wondering is like, you know that that 519 00:29:48,960 --> 00:29:52,120 Speaker 1: makes sense for driving, and it makes sense for AI 520 00:29:52,840 --> 00:29:55,320 Speaker 1: and clearly you know when you think about these five 521 00:29:55,360 --> 00:29:58,360 Speaker 1: areas that you guys are combing through looking for some 522 00:29:58,480 --> 00:30:01,720 Speaker 1: of those things. But the other thing that you brought 523 00:30:01,800 --> 00:30:05,000 Speaker 1: up there was the fact that you're effectively a VC fund, right, 524 00:30:05,240 --> 00:30:07,280 Speaker 1: And so I'm interested in also the fact that, like 525 00:30:07,440 --> 00:30:10,840 Speaker 1: sometimes you might identify something that doesn't come to fruition. 526 00:30:11,440 --> 00:30:14,600 Speaker 1: How often has that happened? Uh? The reason I use 527 00:30:14,720 --> 00:30:16,840 Speaker 1: we are the closest you'll find to a VC fund 528 00:30:17,040 --> 00:30:19,440 Speaker 1: is the time. It's because of our time horizon is 529 00:30:19,600 --> 00:30:23,600 Speaker 1: five years. What what happens before that? Though? The reason 530 00:30:23,720 --> 00:30:29,000 Speaker 1: we have so much of a better um shot at 531 00:30:29,040 --> 00:30:32,360 Speaker 1: a big winner is there's a vetting process that our 532 00:30:32,400 --> 00:30:34,120 Speaker 1: stocks have gone through. It's called the I p O. 533 00:30:34,280 --> 00:30:38,040 Speaker 1: You've got regulators sell side by side bankers. We're not 534 00:30:38,080 --> 00:30:40,400 Speaker 1: going to run into a THEOMS. That's for sure that 535 00:30:40,640 --> 00:30:44,400 Speaker 1: these are products, they really exist. Uh, So I don't 536 00:30:44,480 --> 00:30:47,080 Speaker 1: think we're venture firm in terms of any failures in 537 00:30:47,160 --> 00:30:50,960 Speaker 1: the portfolio, but with time and what's great about having 538 00:30:51,000 --> 00:30:55,360 Speaker 1: a five year time horizon and building autonomous vehicles from 539 00:30:55,400 --> 00:30:59,040 Speaker 1: the bottom up electric vehicles, uh, you know, really understanding 540 00:30:59,080 --> 00:31:02,560 Speaker 1: battery technology G is we can see because of our 541 00:31:02,600 --> 00:31:06,200 Speaker 1: time horizon, we can see where the inefficiencies are in 542 00:31:06,320 --> 00:31:09,480 Speaker 1: the market. One of the biggest is Tesla today. You 543 00:31:09,600 --> 00:31:12,680 Speaker 1: know that we're associated with it UM and it's because 544 00:31:12,720 --> 00:31:17,920 Speaker 1: we've done more work on batteries, artificial intelligence, and data 545 00:31:18,280 --> 00:31:22,520 Speaker 1: big data collection than anyone out there when it when 546 00:31:22,560 --> 00:31:26,520 Speaker 1: it comes to Tesla and and Tesla's competitors, uh, and 547 00:31:26,680 --> 00:31:30,120 Speaker 1: so our confidence is very high. We can't understand why 548 00:31:30,240 --> 00:31:33,360 Speaker 1: people can't see this. The reason they can't see it 549 00:31:33,520 --> 00:31:36,120 Speaker 1: is because they haven't done that research. And the reason 550 00:31:36,160 --> 00:31:39,719 Speaker 1: they haven't done that research is because auto analysts are 551 00:31:39,760 --> 00:31:45,400 Speaker 1: following this, not robotics analysts, not artificial intelligence analysts, uh, 552 00:31:45,600 --> 00:31:48,680 Speaker 1: not big data analysts. So you need a combination, and 553 00:31:48,760 --> 00:31:52,120 Speaker 1: our analysts are our combination. UM. And let me tap 554 00:31:52,160 --> 00:31:56,240 Speaker 1: into Tesla because to me, Tesla hits at many attributes 555 00:31:56,320 --> 00:31:59,160 Speaker 1: that to me set you apart from a typical active 556 00:31:59,200 --> 00:32:02,680 Speaker 1: equity manager for of all, you have bold calls saying 557 00:32:02,720 --> 00:32:05,640 Speaker 1: four thousand is your price target in five years. Um, 558 00:32:05,880 --> 00:32:08,360 Speaker 1: that's bold. Gunlock does the same thing. He's very good 559 00:32:08,400 --> 00:32:11,880 Speaker 1: at bold calls. You know, you gotta breakthrough. A lot 560 00:32:11,920 --> 00:32:14,880 Speaker 1: of people are a lot of competition for attention conviction. 561 00:32:15,640 --> 00:32:18,880 Speaker 1: You bought Tesla even this year when it was down, 562 00:32:19,840 --> 00:32:30,360 Speaker 1: you kept buying transparency, the transparency you show when you 563 00:32:30,480 --> 00:32:32,880 Speaker 1: buy Tesla. You actually put your trades on the site 564 00:32:33,120 --> 00:32:36,080 Speaker 1: every day. You can see the holdings every day. And 565 00:32:36,160 --> 00:32:38,560 Speaker 1: then obviously, you know, the crowdsourcing, the research you put 566 00:32:38,600 --> 00:32:40,640 Speaker 1: out what you think of Tesla. I think you had 567 00:32:40,640 --> 00:32:43,440 Speaker 1: an error somewhere where someone pointed out that actually you 568 00:32:43,520 --> 00:32:45,479 Speaker 1: got fixed. But either way, you're putting it out there. 569 00:32:45,480 --> 00:32:49,680 Speaker 1: You're getting feedback instantly. And then finally, the strong social 570 00:32:49,720 --> 00:32:52,480 Speaker 1: media presence, which you just said. Social media is good 571 00:32:52,520 --> 00:32:54,800 Speaker 1: for you, but you take a lot of crap. I mean, 572 00:32:54,840 --> 00:32:58,280 Speaker 1: I've looked we actually ransom analysis. You're you get more 573 00:32:58,400 --> 00:33:01,800 Speaker 1: tweets than like Rock pretty much, I mean, and a 574 00:33:01,880 --> 00:33:05,080 Speaker 1: lot of them are negative though, mostly because Tesla. You 575 00:33:05,280 --> 00:33:08,440 Speaker 1: just piss people off with the Tesla thing. But anyway, 576 00:33:08,880 --> 00:33:12,200 Speaker 1: an active equity manager at like a t roller leg Mason. 577 00:33:12,240 --> 00:33:14,560 Speaker 1: I just don't see them doing any of those things, 578 00:33:14,720 --> 00:33:17,280 Speaker 1: and it seems like it might be holding them back. 579 00:33:17,520 --> 00:33:19,480 Speaker 1: Maybe they don't have to go all the way you've gone, 580 00:33:19,560 --> 00:33:21,200 Speaker 1: But what do you think is going on there? Why 581 00:33:21,280 --> 00:33:22,960 Speaker 1: do you do it? And yet you don't see many 582 00:33:22,960 --> 00:33:25,520 Speaker 1: stock pickers doing the same. Well a couple of reasons. 583 00:33:25,840 --> 00:33:30,400 Speaker 1: Uh One, their compliance departments will not allow it. Now, 584 00:33:30,560 --> 00:33:33,320 Speaker 1: I think this is a huge competitive advantage for us. 585 00:33:33,480 --> 00:33:37,080 Speaker 1: We are the only one public managers really out there, 586 00:33:37,840 --> 00:33:41,880 Speaker 1: uh that are willing to share our research and talk 587 00:33:41,960 --> 00:33:44,920 Speaker 1: about we can't hype that we have dues and don't 588 00:33:45,080 --> 00:33:48,800 Speaker 1: believe me are chief compliance officer is an attorney who 589 00:33:49,160 --> 00:33:51,640 Speaker 1: spent four years at the SEC when they were evolving 590 00:33:51,760 --> 00:33:55,560 Speaker 1: standards and guidelines for social media and marketing. So he 591 00:33:56,040 --> 00:33:59,040 Speaker 1: is maniacal about making sure we do not say something 592 00:33:59,120 --> 00:34:01,560 Speaker 1: that puts us on the wrong side of regulation. But 593 00:34:01,680 --> 00:34:05,800 Speaker 1: in terms of sharing our research, what has happened I 594 00:34:05,880 --> 00:34:08,080 Speaker 1: believe we're the first sharing economy company in the asset 595 00:34:08,160 --> 00:34:10,600 Speaker 1: management space when it comes to research. What has happened 596 00:34:10,640 --> 00:34:14,880 Speaker 1: now is we're living in the communities were researching because uh, 597 00:34:15,160 --> 00:34:19,120 Speaker 1: we have people who are who are connecting with us 598 00:34:19,160 --> 00:34:21,600 Speaker 1: saying hey, that's our world and yes, you're getting this right, 599 00:34:21,680 --> 00:34:23,800 Speaker 1: or you're not getting that right, and maybe you should 600 00:34:23,800 --> 00:34:27,879 Speaker 1: think about this. Uh. So we are getting insights from 601 00:34:28,280 --> 00:34:33,479 Speaker 1: the the innovators were researching that others cannot get because 602 00:34:33,520 --> 00:34:36,040 Speaker 1: they're not living in those communities and they're not sharing 603 00:34:36,120 --> 00:34:38,640 Speaker 1: what they're doing. I think it is a huge competitive 604 00:34:38,640 --> 00:34:43,120 Speaker 1: advantage and um I think compliance departments will have to 605 00:34:43,400 --> 00:34:46,800 Speaker 1: let up because I do believe Twitter and other social 606 00:34:46,880 --> 00:34:51,480 Speaker 1: networks are going to be very important knowledge networks. And 607 00:34:51,560 --> 00:34:54,399 Speaker 1: this is almost in like contrast to the other kind 608 00:34:54,400 --> 00:34:56,960 Speaker 1: of big sort of theme that we're seeing uh this year, 609 00:34:57,040 --> 00:34:59,799 Speaker 1: which is sort of about active managers looking to get 610 00:34:59,840 --> 00:35:02,920 Speaker 1: in two et f s but not disclose their holdings. 611 00:35:02,960 --> 00:35:05,720 Speaker 1: You know, obviously Presidian kind of coming through and getting 612 00:35:05,760 --> 00:35:08,320 Speaker 1: that approval from the SEC to start these funds. The 613 00:35:08,360 --> 00:35:10,800 Speaker 1: whole idea there is to help active managers into the 614 00:35:10,880 --> 00:35:13,680 Speaker 1: space that previously were put off because they didn't want 615 00:35:13,680 --> 00:35:15,759 Speaker 1: to share that secret source that they feel kind of 616 00:35:15,800 --> 00:35:18,040 Speaker 1: sets them apart. So it's kind of really interesting that 617 00:35:18,360 --> 00:35:20,000 Speaker 1: on the one hand, you have, you know, these funds 618 00:35:20,239 --> 00:35:22,160 Speaker 1: that the Cathy's kind of brought out that have been 619 00:35:22,200 --> 00:35:25,879 Speaker 1: able to deliver these returns and do rely on having 620 00:35:26,080 --> 00:35:28,840 Speaker 1: this kind of crowdsource information. And yet you also have 621 00:35:28,920 --> 00:35:31,440 Speaker 1: at the same time active managers that are trying to 622 00:35:31,880 --> 00:35:34,560 Speaker 1: preserve that secret source and see that as very much 623 00:35:34,640 --> 00:35:38,040 Speaker 1: their way that they can get equivalent returns and deliver 624 00:35:38,160 --> 00:35:41,799 Speaker 1: for investors. And do you think active managers out there 625 00:35:41,800 --> 00:35:44,920 Speaker 1: there's you know, there's six trillion inactive equity funds that 626 00:35:45,000 --> 00:35:47,120 Speaker 1: are eyeing this Presidium model. It's a lot of money. 627 00:35:47,800 --> 00:35:51,480 Speaker 1: Do you think they over estimate the front running issue 628 00:35:52,320 --> 00:35:56,080 Speaker 1: or and or overestimate people even caring about their picks. 629 00:35:57,239 --> 00:36:01,279 Speaker 1: I can tell when we are being played with, you know, 630 00:36:01,520 --> 00:36:05,080 Speaker 1: by high frequency traders or so forth. But that's easy 631 00:36:05,160 --> 00:36:07,080 Speaker 1: to deal with it. As an active manager. You just 632 00:36:07,160 --> 00:36:10,400 Speaker 1: put a limit you don't buy if someone's playing this is. 633 00:36:10,680 --> 00:36:13,600 Speaker 1: This has happened to me my entire career. You know, 634 00:36:14,040 --> 00:36:16,600 Speaker 1: when I used to put give models to the wire 635 00:36:16,680 --> 00:36:19,759 Speaker 1: houses for sam as someone out there knew what we 636 00:36:19,880 --> 00:36:22,480 Speaker 1: were doing. This is. That's why I think it's overstated. 637 00:36:22,560 --> 00:36:25,400 Speaker 1: They all put their portfolios out there every day to 638 00:36:25,520 --> 00:36:28,600 Speaker 1: these wire houses to populate their separately managed account So 639 00:36:28,600 --> 00:36:31,680 Speaker 1: I've never understood that really, uh, And they have control 640 00:36:31,880 --> 00:36:36,040 Speaker 1: limit orders you can do that, so I've never bought that. 641 00:36:36,320 --> 00:36:40,120 Speaker 1: I will say it's easier for us because we're liquidity providers. 642 00:36:40,680 --> 00:36:43,480 Speaker 1: You'll notice what I said, We're quite contrarian in our trading. 643 00:36:43,600 --> 00:36:47,120 Speaker 1: So when when we've got hedge funds dumping all over 644 00:36:47,360 --> 00:36:50,360 Speaker 1: our some of our stocks, we're gonna be buyers that 645 00:36:50,480 --> 00:36:54,120 Speaker 1: if there are high conviction stocks. Same on the other side, Uh, 646 00:36:54,280 --> 00:36:56,080 Speaker 1: we we catch a lot of flaks sometimes when we 647 00:36:56,200 --> 00:36:58,920 Speaker 1: sell as well, because they say, wait a minute, your 648 00:36:58,920 --> 00:37:02,000 Speaker 1: price target is this, and the ideas there's going to 649 00:37:02,080 --> 00:37:04,520 Speaker 1: be controversy around these ideas. You've got the old guard 650 00:37:05,000 --> 00:37:07,279 Speaker 1: and the new guard, and you've got a lot of fear, 651 00:37:07,360 --> 00:37:10,680 Speaker 1: uncertainty and doubt, and you've got new technologies that are 652 00:37:10,760 --> 00:37:12,520 Speaker 1: going to blow away some of the old guards. So 653 00:37:12,719 --> 00:37:14,759 Speaker 1: so there's a big tug of war there, and we 654 00:37:14,880 --> 00:37:18,480 Speaker 1: can play that as a liquidity providers. Others are more 655 00:37:18,640 --> 00:37:21,640 Speaker 1: momentum oriented. They're going to be stopped out if people 656 00:37:21,680 --> 00:37:24,840 Speaker 1: start chasing them. But I just think it's great that active, 657 00:37:24,960 --> 00:37:27,839 Speaker 1: you know, allocating capital to its highest and best use, 658 00:37:28,280 --> 00:37:31,319 Speaker 1: meaning looking to the future, trying to make the world 659 00:37:31,360 --> 00:37:35,480 Speaker 1: a better place. I think active is the next big 660 00:37:35,600 --> 00:37:38,640 Speaker 1: way for e t F S. So you know, personally 661 00:37:38,760 --> 00:37:41,560 Speaker 1: I prefer transparent. And you know why I prefer transparent, 662 00:37:41,760 --> 00:37:45,040 Speaker 1: It is because our clients prefer transparent. They want to 663 00:37:45,080 --> 00:37:48,240 Speaker 1: be a part of this process, they want to understand. 664 00:37:48,480 --> 00:37:51,520 Speaker 1: And you know, we also on Friday's put out any 665 00:37:51,640 --> 00:37:54,840 Speaker 1: stock that's moved up or down more than fifteen percent 666 00:37:55,000 --> 00:37:57,759 Speaker 1: in any day, we put it out there and say, hey, 667 00:37:57,840 --> 00:37:59,840 Speaker 1: this happened. We want you to know why, and you 668 00:38:00,000 --> 00:38:03,080 Speaker 1: know how we feel about it. So I think oh 669 00:38:03,160 --> 00:38:06,920 Speaker 1: eight oh nine caused so much distrust in the financial 670 00:38:07,000 --> 00:38:11,360 Speaker 1: services industry that transparency became paramount. The one thing that 671 00:38:11,520 --> 00:38:14,160 Speaker 1: these active managers who are planning to come over may 672 00:38:14,239 --> 00:38:17,880 Speaker 1: the six trillion. The problem with many of them is 673 00:38:17,960 --> 00:38:23,760 Speaker 1: they are benchmarks sensitive, and I don't believe there's nearly 674 00:38:23,840 --> 00:38:28,120 Speaker 1: as much a market for that as there once was. 675 00:38:28,640 --> 00:38:31,759 Speaker 1: When it comes to active, you've got the whole et 676 00:38:31,880 --> 00:38:36,440 Speaker 1: F industry is fully fulfilling a lot more needs UH 677 00:38:36,600 --> 00:38:39,840 Speaker 1: than than it did in the past. And is you know, 678 00:38:40,040 --> 00:38:43,120 Speaker 1: stealing the march from active if if they're not if 679 00:38:43,160 --> 00:38:46,120 Speaker 1: they're not bold and is speaking of that boldness now? 680 00:38:46,400 --> 00:38:48,760 Speaker 1: I put out a tweet about you're known for tesla 681 00:38:48,840 --> 00:38:51,000 Speaker 1: but some of your other stock picks have actually done 682 00:38:51,040 --> 00:38:53,399 Speaker 1: well and offset some of the Tesla losses this year. 683 00:38:53,760 --> 00:38:56,759 Speaker 1: You're up at a r k K since launching, and 684 00:38:56,960 --> 00:39:00,600 Speaker 1: SMP is up. But that's a lot of beta names 685 00:39:00,640 --> 00:39:03,319 Speaker 1: like this could reverse. Like let's say the fed Raises has, 686 00:39:03,480 --> 00:39:05,400 Speaker 1: you know, like a two thous eight but on steroids. 687 00:39:06,280 --> 00:39:08,759 Speaker 1: Somebody replied to me and said, won't end well, like 688 00:39:08,880 --> 00:39:11,440 Speaker 1: we've seen this before the Janice twenty. What do you 689 00:39:11,520 --> 00:39:14,760 Speaker 1: say to those skeptics that this high active share, high octane, 690 00:39:14,840 --> 00:39:18,719 Speaker 1: high beta methodology has a downside. Well, I that is 691 00:39:18,840 --> 00:39:21,360 Speaker 1: why I like to trade these names. We like to 692 00:39:21,480 --> 00:39:25,480 Speaker 1: again lie in wait. But when it comes to disruptive innovation, 693 00:39:25,640 --> 00:39:28,640 Speaker 1: if we get into a really turbulent period oh eight 694 00:39:28,680 --> 00:39:32,759 Speaker 1: o nine perfect example, because our names are not big 695 00:39:32,920 --> 00:39:35,520 Speaker 1: names in the indices, they are going to be hurt 696 00:39:35,600 --> 00:39:39,200 Speaker 1: disproportionately in the beginning of that move down. But oh 697 00:39:39,320 --> 00:39:42,200 Speaker 1: eight O nine was very instructive. Now I was at 698 00:39:42,280 --> 00:39:45,800 Speaker 1: another firm at the time, but we started out and 699 00:39:46,000 --> 00:39:49,160 Speaker 1: and we were had moved much more towards disruptive innovation 700 00:39:49,280 --> 00:39:55,440 Speaker 1: technologically enabled. We started out performing November eight and in 701 00:39:55,520 --> 00:39:58,640 Speaker 1: the first quarter oh nine, when the market was down 702 00:39:58,680 --> 00:40:03,000 Speaker 1: ten percent. We were flat. Why it's because cooler heads prevailed. 703 00:40:03,560 --> 00:40:07,400 Speaker 1: Analysts and portfolio managers started looking at the fundamentals, and 704 00:40:07,560 --> 00:40:12,840 Speaker 1: they learned that Amazon's worst quarter worst remember Amazon was 705 00:40:13,360 --> 00:40:17,120 Speaker 1: destroyed back then. Amazon's worst quarter as retail sales were 706 00:40:17,160 --> 00:40:22,480 Speaker 1: down ten Amazon's worst quarter was up four Salesforce dot 707 00:40:22,520 --> 00:40:28,040 Speaker 1: COM's worst quarter when tech spending was down up revenue growth, 708 00:40:28,120 --> 00:40:30,320 Speaker 1: but even though it had been destroyed. So they started 709 00:40:30,480 --> 00:40:34,680 Speaker 1: they started looking at the fundamentals. Our companies gain traction 710 00:40:34,920 --> 00:40:40,160 Speaker 1: because they're better, cheaper, faster, more productive and gained tremendous 711 00:40:40,239 --> 00:40:44,040 Speaker 1: share during downturns. So when we first met, we were 712 00:40:44,080 --> 00:40:46,759 Speaker 1: talking about bitcoin, and I know that you kind of 713 00:40:46,800 --> 00:40:49,640 Speaker 1: sold down Bitcoin and kind of reduced your positions in 714 00:40:49,719 --> 00:40:53,280 Speaker 1: that as we came off those those incredibly meteorit chives. Obviously, 715 00:40:53,320 --> 00:40:55,600 Speaker 1: bitcoin's back in the news again. It's been going back 716 00:40:55,680 --> 00:40:58,319 Speaker 1: up again. Have you guys been increasing your holdings? Where 717 00:40:58,320 --> 00:41:01,160 Speaker 1: do you see bitcoin at the moment? This is very important, 718 00:41:01,440 --> 00:41:05,879 Speaker 1: UH Forum investors to understand what we learned in two 719 00:41:05,880 --> 00:41:08,160 Speaker 1: thousands seventeen. And we had the wild Rider right and 720 00:41:08,280 --> 00:41:11,080 Speaker 1: we cut it at a great time, But we almost 721 00:41:11,200 --> 00:41:14,000 Speaker 1: had to because when it started for King, we learned 722 00:41:14,239 --> 00:41:17,920 Speaker 1: that we had unqualified income, and when it hit ten 723 00:41:17,960 --> 00:41:20,160 Speaker 1: percent of our funds, we had to sell it below 724 00:41:20,239 --> 00:41:26,000 Speaker 1: that that created unqualified income. Only ten percent of gross 725 00:41:26,239 --> 00:41:29,239 Speaker 1: profits can be in the form of unqualified income. The 726 00:41:29,360 --> 00:41:32,320 Speaker 1: rest will be confiscated by the I r S. So 727 00:41:32,480 --> 00:41:35,839 Speaker 1: we have taken it. This is simply because of we're 728 00:41:35,880 --> 00:41:38,480 Speaker 1: a registered investment company and these are forty ACT funds, 729 00:41:38,920 --> 00:41:40,759 Speaker 1: so we've taken it out of a r k K. 730 00:41:41,560 --> 00:41:45,600 Speaker 1: We've minimized it in a rk W. It's about a 731 00:41:45,640 --> 00:41:49,760 Speaker 1: two percent position in our discretionary accounts separately managed accounts. 732 00:41:49,800 --> 00:41:52,399 Speaker 1: It's our number two position at an eight percent weight. 733 00:41:52,920 --> 00:41:56,719 Speaker 1: Our conviction and bitcoin has only increased in the last 734 00:41:56,760 --> 00:41:59,800 Speaker 1: two years. We think it is. It is being battled 735 00:42:00,040 --> 00:42:03,759 Speaker 1: did as the global digital currency, and there will only 736 00:42:03,880 --> 00:42:10,239 Speaker 1: be a few cryptocurrencies at the end of the day. Okay, So, 737 00:42:10,560 --> 00:42:14,040 Speaker 1: so another but bold call. But I want you to 738 00:42:14,120 --> 00:42:17,279 Speaker 1: be bold and look yourself in the mirror. You're We've 739 00:42:17,480 --> 00:42:20,600 Speaker 1: talked a lot about the future. Five years from now, Cathy, 740 00:42:20,800 --> 00:42:24,319 Speaker 1: what what does Cathy look like? What does our look like? Well, 741 00:42:24,440 --> 00:42:27,720 Speaker 1: I I love the way our research ecosystem is evolving 742 00:42:27,840 --> 00:42:32,840 Speaker 1: to embrace universities and venture capitalists are coming in because 743 00:42:32,920 --> 00:42:36,480 Speaker 1: they know we're doing the first principles research that is 744 00:42:36,560 --> 00:42:39,359 Speaker 1: not done enough out there. So I really want our 745 00:42:39,440 --> 00:42:42,960 Speaker 1: research ecode system to flourish, partly because one of our 746 00:42:43,040 --> 00:42:47,320 Speaker 1: missions and values is to educate and educate our investor 747 00:42:47,400 --> 00:42:52,719 Speaker 1: base and really increase the efficiencies in uh an inefficiently 748 00:42:52,800 --> 00:42:56,439 Speaker 1: price market right now, so so that, of course we'd 749 00:42:56,480 --> 00:42:58,839 Speaker 1: love to scale globally. We're doing that right now. As 750 00:42:58,880 --> 00:43:02,280 Speaker 1: I mentioned, more than half of our assets are outside 751 00:43:02,400 --> 00:43:05,239 Speaker 1: the United States. UM, we'd like to do more in 752 00:43:05,400 --> 00:43:08,839 Speaker 1: terms of education. UM, you know our capacity. We get 753 00:43:09,000 --> 00:43:12,480 Speaker 1: asked about capacity a lot, and UH people say, well, 754 00:43:12,520 --> 00:43:16,359 Speaker 1: this is niche capacity, you know. It's if we are 755 00:43:16,520 --> 00:43:21,680 Speaker 1: right and these innovation platforms are are ready for prime 756 00:43:21,760 --> 00:43:25,919 Speaker 1: time and are scaling exponentially, our capacities should be able 757 00:43:25,960 --> 00:43:28,719 Speaker 1: to scale exponentially as well, so we do not have 758 00:43:28,800 --> 00:43:33,000 Speaker 1: the capacity problem that a lot of other managers might have. 759 00:43:33,440 --> 00:43:35,920 Speaker 1: And then just on a personal basis in terms of 760 00:43:36,040 --> 00:43:40,680 Speaker 1: this innovation, I have found it so interesting since starting 761 00:43:40,719 --> 00:43:43,480 Speaker 1: the firm in the early days, I had a lot 762 00:43:43,560 --> 00:43:47,520 Speaker 1: of self selection women asking you know, to join. Now 763 00:43:47,640 --> 00:43:51,640 Speaker 1: that we've been this successful. I'm getting fewer women much 764 00:43:51,760 --> 00:43:55,279 Speaker 1: more men. And so one of my objectives, and I've 765 00:43:55,320 --> 00:43:57,279 Speaker 1: already started this in my high school. I went to 766 00:43:57,320 --> 00:44:00,279 Speaker 1: an all girl high school. Is I've started at an 767 00:44:00,320 --> 00:44:05,360 Speaker 1: innovation center in my father's honor. He's the radar expert 768 00:44:05,440 --> 00:44:09,799 Speaker 1: and my inspiration. Uh. And I want to inspire these 769 00:44:09,880 --> 00:44:14,160 Speaker 1: girls with a curriculum around disruptive innovation so that they 770 00:44:14,200 --> 00:44:16,880 Speaker 1: are inspired at a young enough age to really just 771 00:44:17,160 --> 00:44:20,200 Speaker 1: want it and want to run hard with it. Uh. 772 00:44:20,360 --> 00:44:23,400 Speaker 1: So that's just on a little personal note. But I 773 00:44:23,560 --> 00:44:26,600 Speaker 1: think I think you know, if you compare what's happening today, 774 00:44:27,280 --> 00:44:29,520 Speaker 1: uh with any other time in history, First you have 775 00:44:29,600 --> 00:44:34,640 Speaker 1: to go back to the late eighteen hundreds, early nine hundreds, uh, telephone, electricity, 776 00:44:34,680 --> 00:44:38,320 Speaker 1: internal combustion engine. If you look at the amount of 777 00:44:38,400 --> 00:44:40,120 Speaker 1: innovation that's going to take place today, we have a 778 00:44:40,120 --> 00:44:42,560 Speaker 1: paper on this on our site. UH. And if you 779 00:44:42,719 --> 00:44:45,880 Speaker 1: use a Richter scale for your to try and understand 780 00:44:45,960 --> 00:44:49,040 Speaker 1: how different this is going to be, you would measure 781 00:44:49,480 --> 00:44:54,840 Speaker 1: the fifty years ended at uh maybe a six or 782 00:44:54,920 --> 00:44:57,280 Speaker 1: six and a half. But in terms of what's about 783 00:44:57,360 --> 00:45:00,480 Speaker 1: to happen, I think it's going to measure an eight 784 00:45:00,680 --> 00:45:03,160 Speaker 1: or nine. Now, you never want to be in an 785 00:45:03,239 --> 00:45:06,439 Speaker 1: earthquake like that. You want to you don't. In other words, 786 00:45:06,480 --> 00:45:08,759 Speaker 1: you do not want to be disrupted. You want to 787 00:45:08,840 --> 00:45:12,160 Speaker 1: embrace this change. And uh, you know this is not 788 00:45:12,440 --> 00:45:15,880 Speaker 1: a linear you know six to eight or nine is 789 00:45:15,960 --> 00:45:20,279 Speaker 1: not linear. This is an exponential change. So I really 790 00:45:20,360 --> 00:45:23,320 Speaker 1: feel every portfolio needs exposure to it. And you know, 791 00:45:23,400 --> 00:45:26,360 Speaker 1: we'd like we'd like to be a part of that. Okay, 792 00:45:26,480 --> 00:45:29,400 Speaker 1: there you go, Cathy, Rachel, thanks for joining us a trillion, 793 00:45:29,640 --> 00:45:31,560 Speaker 1: Thank you for having me, Thanks for having a fun, 794 00:45:35,920 --> 00:45:38,799 Speaker 1: Thanks for listening to Trillions until next time. You can 795 00:45:38,840 --> 00:45:43,400 Speaker 1: find us on the Bloomberg Terminal, Bloomberg dot com, Apple Podcast, Spotify, 796 00:45:43,840 --> 00:45:46,360 Speaker 1: and wherever else you'd like to listen. We'd love to 797 00:45:46,440 --> 00:45:49,799 Speaker 1: hear from you. We're on Twitter, I'm at Joel Webber Show. 798 00:45:50,280 --> 00:45:54,440 Speaker 1: He's at Eric Fautunus. You can find Kathy at Kathy 799 00:45:54,560 --> 00:45:57,080 Speaker 1: d Wood that's Kathy with the C and an i 800 00:45:57,280 --> 00:46:00,880 Speaker 1: E as well as at ARC invest and Rachel is 801 00:46:01,360 --> 00:46:06,279 Speaker 1: at Rachel Evans Underscore and Why. Trillions is produced by 802 00:46:06,360 --> 00:46:10,520 Speaker 1: Magnus Hendrickson. Francesca Levy is the head of Bloomberg Podcast. 803 00:46:10,960 --> 00:46:11,240 Speaker 1: Bye